Efficiency Evaluation of ChatGPT for Adverb Type Categorization
Walelign Tewabe Sewunetie, László Kovács · 2023
Recent generative pre-trained transformer models provide outstanding performance in many different natural language tasks. This paper presents an evaluation of the efficiency of the ChatGPT 3.5 language model, and Dictionary and ML-based methods, in the task of adverb type categorization within natural language processing. This evaluation provides insights into the strengths and weaknesses of ChatGPT 3.5 and its potential applications in English sentence parsing and language understanding tasks. In this evaluation scenario, the average test score for the ChatGPT-based method is found to be 3.5 out of 5, indicating the overall evaluation by the experts. Similarly, the Dictionary and ML-based method achieves an average test score of 3.6 out of 5, reflecting the collective assessment by the evaluators. These findings of our test results contribute to our understanding of the performance and effectiveness of both approaches in adverb-type categorization.